SISTEM PENDUKUNG KEPUTUSAN PENENTUAN TAMBAH STOK BARANG MENGGUNAKAN METODE TOPSIS BERBASIS ANDROID
Abstract
Inefficient stock management can lead to problems such as overstocking or stockouts, incorrect pricing, and difficulties in identifying best-selling products, which negatively affect the performance and profitability of Toko Twins Pancing Temanggung while reducing customer satisfaction. To overcome these issues, this study develops a mobile-based decision support system (DSS) using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, designed to assist store owners in determining stock additions, managing inventory, and identifying best-selling products. The steps taken include problem identification, data collection, system architecture design, TOPSIS implementation, and system testing. TOPSIS was selected for its ability to provide accurate recommendations by considering various relevant criteria. Decision-making is influenced by factors such as price, stock quantity, and weekly sales. The study results indicate that this system can effectively recommend stock additions by prioritizing products with sufficient stock and good sales performance. For example, the product with the highest preference value is the Red Angle fishing rod (0.8963), which is prioritized for restocking. The system, tested with data from Toko Twins Pancing Temanggung, achieved a 98% accuracy rate compared to manual calculations. Users can conveniently access this system via mobile devices, enabling decision-making anytime and anywhere. This DSS enhances operational efficiency and business performance at Toko Twins Pancing Temanggung, providing a significant solution for stock management and offering a more structured and efficient approach to achieving higher profits.
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